Protein Mechanics: A New Frontier in Biomechanics

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination

Proteins play a crucial role in many biological processes, where their interaction with other proteins are integral. Abnormal protein-protein interactions (PPIs) have been linked to various diseases including cancer, and thus targeting PPIs holds promise for drug development. However, experimental confirmation of the peculiarities of PPIs is challenging due to their dynamic and transient nature. As a complement to experimental technologies, multiple computational molecular docking (MD) methods have been developed to predict the structures of protein-protein complexes and their dynamics, still requiring further improvements in several issues. Here, we report an improved MD method, namely three-software docking (3SD), by employing three popular protein-peptide docking software (CABS-dock, HPEPDOCK, and HADDOCK) in combination to ensure constant quality for most targets. We validated our 3SD performance in known protein-peptide interactions (PpIs). We also enhanced MD performance in proteins having intrinsically disordered regions (IDRs) by applying the modified 3SD strategy, the three-software docking after removing random coiled IDR (3SD-RR), to the comparable crystal PpI structures. At the end, we applied 3SD-RR to the AlphaFold2-predicted receptors, yielding an efficient prediction of PpI pose with high relevance to the experimental data regardless of the presence of IDRs or the availability of receptor structures. Our study provides an improved solution to the challenges in studying PPIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery. SIGNIFICANCE STATEMENT: Protein-protein interactions (PPIs) are integral to life, and abnormal PPIs are associated with diseases such as cancer. Studying protein-peptide interactions (PpIs) is challenging due to their dynamic and transient nature. Here we developed improved docking methods (3SD and 3SD-RR) to predict the PpI poses, ensuring constant quality in most targets and also addressing issues like intrinsically disordered regions (IDRs) and artificial intelligence-predicted structures. Our study provides an improved solution to the challenges in studying PpIs through computational docking and has the potential to contribute to PPIs-targeted drug discovery.

Persistence length of α-helical poly-L-lysine

The α-helix has a significant role in protein function and structure because of its rigidity. In this study, we investigate the persistence length, l_p, of α-helical poly-L-lysine, PLL, for two molecular weights. PLL experiences a random coil-helix transition as the pH is raised from 7 to 12. Using light scattering experiments to determine the radius of gyration (R_g), hydrodynamic radius, (R_h), the shape factor (R_g/R_h), and second virial coefficient (A₂), and circular dichroism to determine the helical content, we find the structure and l_p of PLL as a function of pH (7.4-11.4) and ionic strength (100-166 mM). With increasing pH, we find an increase in l_p from 2 nm to 15-21 nm because of α-helix formation. We performed dissipative particle dynamics (DPD) simulations and found a similar increase in l_p. While this l_p is less than that predicted by molecular dynamics simulations, it is consistent with other experimental results, which quantify the mechanics of α-helices. By determining the mechanics of helical polypeptides like PLL, we can further understand their implications to protein function.

Origin of Cancer: Cell work is the Key to Understanding Cancer Initiation and Progression

The cell is the smallest unit of life. It is a structure that maintains order through self-organization, characterized by a high level of dynamism, which in turn is characterized by work. For this work to take place, a continuous high flow of energy is necessary. However, a focused view of the physical relationship between energy and work is inadequate for describing complex biological/medical mechanisms or systems. In this review, we try to make a connection between the fundamental laws of physics and the mechanisms and functions of biology, which are characterized by self-organization. Many different physical work processes (work) in human cells are called cell work and can be grouped into five forms: synthetic, mechanical, electrical, concentration, and heat generation cell work. In addition to the flow of energy, these cell functions are based on fundamental processes of self-organization that we summarize with the term Entirety of molecular interaction (EoMI). This illustrates that cell work is caused by numerous molecular reactions, flow equilibrium, and mechanisms. Their number and interactions are so complex that they elude our perception in their entirety. To be able to describe cell functions in a biological/medical context, the parameters influencing cell work should be summarized in overarching influencing variables. These are “biological” energy, information, matter, and cell mechanics (EMIM). This makes it possible to describe and characterize the cell work involved in cell systems (e.g., respiratory chain, signal transmission, cell structure, or inheritance processes) and to demonstrate changes. If cell work and the different influencing parameters (EMIM influencing variables) are taken as the central property of the cell, specific gene mutations cannot be regarded as the sole cause for the initiation and progression of cancer. This reductionistic monocausal view does not do justice to the dynamic and highly complex system of a cell. Therefore, we postulate that each of the EMIM influencing variables described above is capable of changing the cell work and thus the order of a cell in such a way that it can develop into a cancer cell.

The biophysics of cancer: emerging insights from micro- and nanoscale tools

Cancer is a complex and dynamic disease that is aberrant both biologically and physically. There is growing appreciation that physical abnormalities with both cancer cells and their microenvironment that span multiple length scales are important drivers for cancer growth and metastasis. The scope of this review is to highlight the key advancements in micro- and nano-scale tools for delineating the cause and consequences of the aberrant physical properties of tumors. We focus our review on three important physical aspects of cancer: 1) solid mechanical properties, 2) fluid mechanical properties, and 3) mechanical alterations to cancer cells. Beyond posing physical barriers to the delivery of cancer therapeutics, these properties are also known to influence numerous biological processes, including cancer cell invasion and migration leading to metastasis, and response and resistance to therapy. We comment on how micro- and nanoscale tools have transformed our fundamental understanding of the physical dynamics of cancer progression and their potential for bridging towards future applications at the interface of oncology and physical sciences.

Effects of Non-thermal Ultrasound on a Fibroblast Monolayer Culture: Influence of Pulse Number and Pulse Repetition Frequency

Despite the use of therapeutic ultrasound in the treatment of soft tissue pathologies, there remains some controversy regarding its efficacy. In order to develop new treatment protocols, it is a common practice to carry out in vitro studies in cell cultures before conducting animal tests. The lack of reproducibility of the experimental results observed in the literature concerning in vitro experiments motivated us to establish a methodology for characterizing the acoustic field in culture plate wells. In this work, such acoustic fields are fully characterized in a real experimental configuration, with the transducer being placed in contact with the surface of a standard 12-well culture plate. To study the non-thermal effects of ultrasound on fibroblasts, two different treatment protocols are proposed: long pulse (200 cycles) signals, which give rise to a standing wave in the well with the presence of cavitation (I_SPTP max = 19.25 W/cm²), and a short pulse (five cycles) of high acoustic pressure, which produces a number of echoes in the cavity (I_SPTP = 33.1 W/cm², with P_max = 1.01 MPa). The influence of the acoustic intensity, the number of pulses, and the pulse repetition frequency was studied. We further analyzed the correlation of these acoustic parameters with cell viability, population, occupied surface, and cell morphology. Lytic effects when cavitation was present, as well as mechanotransduction reactions, were observed.

Transmembrane Helices Tilt, Bend, Slide, Torque, and Unwind between Functional States of Rhodopsin

The seven-helical bundle of rhodopsin and other G-protein coupled receptors undergoes structural rearrangements as the transmembrane receptor protein is activated. These structural changes are known to involve tilting and bending of various transmembrane helices. However, the cause and effect relationship among structural events leading to a cytoplasmic crevasse for G-protein binding is less well defined. Here we present a mathematical model of the protein helix and a simple procedure to determine multiple parameters that offer precise depiction of a helical conformation. A comprehensive survey of bovine rhodopsin structures shows that the helical rearrangements during the activation of rhodopsin involve a variety of angular and linear motions such as torsion, unwinding, and sliding in addition to the previously reported tilting and bending. These hitherto undefined motion components unify the results obtained from different experimental approaches, and demonstrate conformational similarity between the active opsin structure and the photoactivated structures in crystallo near the retinal anchor despite their marked differences.

The Power of Force: Insights into the Protein Folding Process Using Single-Molecule Force Spectroscopy

One of the major challenges in modern biophysics is observing and understanding conformational changes during complex molecular processes, from the fundamental protein folding to the function of molecular machines. Single-molecule techniques have been one of the major driving forces of the huge progress attained in the last few years. Recent advances in resolution of the experimental setups, aided by theoretical developments and molecular dynamics simulations, have revealed a much higher degree of complexity inside these molecular processes than previously reported using traditional ensemble measurements. This review sums up the evolution of these developments and gives an outlook on prospective discoveries.

Asymmetric dynamics of ion channel forming proteins - Hepatitis C virus (HCV) p7 bundles

Protein p7 of hepatitis C virus (HCV) is a short 63 amino acid membrane protein which homo-oligomerises in the lipid membrane to form ion and proton conducting bundles. Two different genotypes (GTs) of p7, 1a and 5a, are used to simulate hexameric bundles of the protein embedded in a fully hydrated lipid bilayer during 400 ns molecular dynamics (MD) simulations. Whilst the bundle of GT 1a is based on a fully computational derived structure, the bundle of GT 5a is based on NMR spectroscopic data. Results of a full correlation analysis (FCA) reveal that albeit structural differences both bundles screen local minima during the simulation. The collective motion of the protein domains is asymmetric. No 'breathing-mode'-like dynamics is observed. The presence of divalent ions, such as Ca-ions affects the dynamics of especially solvent exposed parts of the protein, but leaves the asymmetric domain motion unaffected.

Toward the identification of molecular cogs

Computer simulations of molecular systems allow determination of microscopic interactions between individual atoms or groups of atoms, as well as studies of intramolecular motions. Nevertheless, description of structural transformations at the mezoscopic level and identification of causal relations associated with these transformations is very difficult. Structural and functional properties are related to free energy changes. Therefore, to better understand structural and functional properties of molecular systems, it is required to deepen our knowledge of free energy contributions arising from molecular subsystems in the course of structural transformations. The method presented in this work quantifies the energetic contribution of each pair of atoms to the total free energy change along a given collective variable. Next, with the help of a genetic clustering algorithm, the method proposes a division of the system into two groups of atoms referred to as molecular cogs. Atoms which cooperate to push the system forward along a collective variable are referred to as forward cogs, and those which work in the opposite direction as reverse cogs. The procedure was tested on several small molecules for which the genetic clustering algorithm successfully found optimal partitionings into molecular cogs. The primary result of the method is a plot depicting the energetic contributions of the identified molecular cogs to the total Potential of Mean Force (PMF) change. Case-studies presented in this work should help better understand the implications of our approach, and were intended to pave the way to a future, publicly available implementation.

Probing the effect of force on HIV-1 receptor CD4

Cell-surface proteins are central for the interaction of cells with their surroundings and are also associated with numerous diseases. These molecules are exposed to mechanical forces, but the exact relation between force and the functions and pathologies associated with cell-surface proteins is unclear. An important cell-surface protein is CD4, the primary receptor of HIV-1. Here we show that mechanical force activates conformational and chemical changes on CD4 that may be important during viral attachment. We have used single-molecule force spectroscopy and analysis on HIV-1 infectivity to demonstrate that the mechanical extension of CD4 occurs in a time-dependent manner and correlates with HIV-1 infectivity. We show that Ibalizumab, a monoclonal antibody that blocks HIV-1, prevents the mechanical extension of CD4 domains 1 and 2. Furthermore, we demonstrate that thiol/disulfide exchange in CD4 requires force for exposure of cryptic disulfide bonds. This mechanical perspective provides unprecedented information that can change our understanding on how viruses interact with their hosts.

The intrinsic dynamics of Cse1p and Xpot elucidated by coarse-grained models

Cse1p and Xpot are two karyopherin proteins that transport the corresponding cargos during the nucleocytoplasmic transport. We utilized Elastic Network Model (ENM) and Finite Element Analysis (FEA) to study their conformational dynamics. These dynamics were interpreted by their intrinsic modes that played key roles in the flexibility of karyopherins, which further affected the binding affinities. The findings included that it was the karyopherin's versatile conformations composed of the same superhelices of HEAT repeats that produced different degrees of functional flexibilities. We presented evidence that these coarse-grained methods could help to elucidate the biological function behind the structures of the two karyopherins.

Stretchy proteins on stretchy substrates: the important elements of integrin-mediated rigidity sensing

Matrix and tissue rigidity guides many cellular processes, including the differentiation of stem cells and the migration of cells in health and disease. Cells actively and transiently test rigidity using mechanisms limited by inherent physical parameters that include the strength of extracellular attachments, the pulling capacity on these attachments, and the sensitivity of the mechanotransduction system. Here, we focus on rigidity sensing mediated through the integrin family of extracellular matrix receptors and linked proteins and discuss the evidence supporting these proteins as mechanosensors.

Integration of statistical modeling and high-content microscopy to systematically investigate cell-substrate interactions

Cell-substrate interactions are multifaceted, involving the integration of various physical and biochemical signals. The interactions among these microenvironmental factors cannot be facilely elucidated and quantified by conventional experimentation, and necessitate multifactorial strategies. Here we describe an approach that integrates statistical design and analysis of experiments with automated microscopy to systematically investigate the combinatorial effects of substrate-derived stimuli (substrate stiffness and matrix protein concentration) on mesenchymal stem cell (MSC) spreading, proliferation and osteogenic differentiation. C3H10T1/2 cells were grown on type I collagen- or fibronectin-coated polyacrylamide hydrogels with tunable mechanical properties. Experimental conditions, which were defined according to central composite design, consisted of specific permutations of substrate stiffness (3-144 kPa) and adhesion protein concentration (7-520 microg/mL). Spreading area, BrdU incorporation and Runx2 nuclear translocation were quantified using high-content microscopy and modeled as mathematical functions of substrate stiffness and protein concentration. The resulting response surfaces revealed distinct patterns of protein-specific, substrate stiffness-dependent modulation of MSC proliferation and differentiation, demonstrating the advantage of statistical modeling in the detection and description of higher-order cellular responses. In a broader context, this approach can be adapted to study other types of cell-material interactions and can facilitate the efficient screening and optimization of substrate properties for applications involving cell-material interfaces.